Instructions to use mradermacher/colbertv2.0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/colbertv2.0-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("feature-extraction", model="mradermacher/colbertv2.0-GGUF")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/colbertv2.0-GGUF", device_map="auto")

sentence-transformers

How to use mradermacher/colbertv2.0-GGUF with sentence-transformers:

from pylate import models

queries = [
    "Which planet is known as the Red Planet?",
    "What is the largest planet in our solar system?",
]

documents = [
    ["Mars is the Red Planet.", "Venus is Earth's twin."],
    ["Jupiter is the largest planet.", "Saturn has rings."],
]

model = models.ColBERT(model_name_or_path="mradermacher/colbertv2.0-GGUF")

queries_emb = model.encode(queries, is_query=True)
docs_emb = model.encode(documents, is_query=False)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mradermacher/colbertv2.0-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mradermacher/colbertv2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/colbertv2.0-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mradermacher/colbertv2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/colbertv2.0-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf mradermacher/colbertv2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/colbertv2.0-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf mradermacher/colbertv2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/colbertv2.0-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/colbertv2.0-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/colbertv2.0-GGUF with Ollama:
```
ollama run hf.co/mradermacher/colbertv2.0-GGUF:Q4_K_M
```

Unsloth Studio

How to use mradermacher/colbertv2.0-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for mradermacher/colbertv2.0-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for mradermacher/colbertv2.0-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mradermacher/colbertv2.0-GGUF to start chatting

Docker Model Runner
How to use mradermacher/colbertv2.0-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/colbertv2.0-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/colbertv2.0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/colbertv2.0-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.colbertv2.0-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

mradermacher commited on Mar 3, 2025

Commit

dadb008

verified ·

1 Parent(s): 4ab43c3

uploaded from rain

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Files changed (13) hide show

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